IPA Fall Release 2014

Pathway Activity Analysis: Predict the activity of Canonical Pathways

Take pathway analysis to the next level with the IPA Fall 2014 Release. Identify significant scientific discoveries from more than just an enrichment p-value; quickly predict if Canonical Pathways, including functional end-points, are increased or decreased based on differentially expressed genes or proteins in your dataset.

The bars in the Canonical Pathway bar chart are now colored to indicate their new activation z-scores. Orange bars predict an overall increase in the activity of the pathway while blue bars indicate a prediction of an overall decrease in activity.

Pathway Activity Analysis. In this release, bar charts in Canonical Pathway Analysis indicate the activation state of Canonical Pathways. Orange bars or blue bars (not shown) predict an increase or decrease in a pathway’s activity, respectively. Gray bars indicate pathways where predictions are not currently possible. If you click on a pathway bar, you will see the genes in your dataset that overlap with that Canonical Pathway. The new “Expected” column indicates the state that gene is predicted to have if the pathway were activated.

PathTracer enables you to quickly highlight relationships and nodes of interest within networks and pathways. In complex visual representations of biological systems, sometimes it is difficult to see the paths (relationships) among molecules or other items of interest. PathTracer makes this dramatically easier by fading away less interesting areas of a network or pathway, and highlighting the sub-network of interest.

Example of a Regulator Effects network with PathTracer turned on and MiR-200b-3p selected. The “focus” of PathTracer has been set to 2 steps, meaning that nodes up to two steps away from the selected nodes are opaque (fully visible) and others outside of the focus are partially faded. Now the paths and intervening nodes from MiR to the four functions are easily seen.

PathTracer enables you to select one or more nodes and specify how many steps to traverse along the network away from the selected node(s). Those nodes connected within the specified number of steps remain opaque (fully visible). You can choose to traverse the network upstream, downstream, or in both directions. You can also choose how much to fade the more distant / unconnected nodes. Furthermore, you can select the opaque nodes and either keep or delete them if desired.

BioProfiler*: Start with molecules or a dataset to explore detailed biological roles

BioProfiler in IPA helps you quickly explore the detailed relationships between molecules and their associated diseases, functions, or phenotypes. This can help identify potential drug targets or targets of toxicity, drugs-disease relationships, and biomarkers. Now, start your workflow with one or more molecules of interest including those in a dataset. Or, start with a disease/function, and limit the results to the molecules that are in a selected dataset.

Starting BioProfiler from a dataset

Relationship Export*: Export relationships from networks and pathways for further visualization

The new Relationship Export capability in IPA enables you to export the structural information contained within IPA networks or pathways for visualization in other tools such as Cytoscape. The export format contains relationships modeled as triples: Node A -> Relationship -> Node B.

[*] Included with Advanced Analytics which is available at additional cost